Synthesis Of Spatio-temporal Models By The Evolution Of Non-uniform Cellular Automata

dc.creatorRomano A.L.
dc.creatorVillanueva W.J.
dc.creatorZanetti M.S.
dc.creatorVon Zuben F.J.
dc.date2009
dc.date2015-06-26T13:34:09Z
dc.date2015-11-26T14:59:09Z
dc.date2015-06-26T13:34:09Z
dc.date2015-11-26T14:59:09Z
dc.date.accessioned2018-03-28T22:10:45Z
dc.date.available2018-03-28T22:10:45Z
dc.identifier9783642010873
dc.identifierStudies In Computational Intelligence. Springer Verlag, v. 204, n. , p. 85 - 104, 2009.
dc.identifier1860949X
dc.identifier10.1007/978-3-642-01088-0_4
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-65549166536&partnerID=40&md5=a3f473bad0e455eb0bd3e978518c999d
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/91901
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/91901
dc.identifier2-s2.0-65549166536
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1255994
dc.descriptionNon-uniform or inhomogeneous cellular automata (NunCA) [28] are spatio-temporal models for dynamical systems in which space and time are discrete, and there is a distinct transition rule for each cell, with a finite number of states. The cells are in a regular lattice and the transition from one state to another is performed synchronously. The next state of a given cell will then be provided by a local and fixed transition rule that associates its current state and the current state of the neighbouring cells with the next state. The neighbourhood could also be specific for each cell, but will be considered the same, except for the cells at the frontiers of the regular lattice. So, the only distinct feature between NunCA and the traditional uniform cellular automata (CA) [29,34] is the adoption of a specific transition rule for each cell instead of a single transition rule for all the cells in the lattice. © 2009 Springer-Verlag Berlin Heidelberg.
dc.description204
dc.description
dc.description85
dc.description104
dc.descriptionBäck, T., Hoffmeister, F., Schwefel, H.-P., Survey of Evolution Strategies (1991) Proceedings of the 4th International Conference on Genetic Algorithms, pp. 2-9
dc.descriptionBasanta, D., Miodownik, M.A., Bentley, P.J., Holm, E.A., Investigating the Evolvability of Biologically Inspired CA (2004) Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems, ALIFE9
dc.descriptionBeyer, H., Schwefel, H., (2002) Evolution strategies: A comprehensive introduction, , Natural Computing
dc.descriptionCamazine, S., Deneubourg, J.-L., Franks, N.R., Sneyd, J., Theraulaz, G., Bonabeau, E., (2001) Self-Organization in Biological Systems, , Princeton University Press, Princeton
dc.descriptionChua, L.O., Yang, L., Cellular Neural Networks: Theory (1988) IEEE Transactions on Circuits and Systems, 35 (10), pp. 1257-1272
dc.descriptionChopard, B., (1998) Cellular automata modeling of physical systems, , Cambridge University Press, Cambridge
dc.descriptionCollasanti, R.L., Grime, J.P., Resource dynamics and vegetation process: A deterministic model using two-dimensional cellular automata (1993) Functional Ecology, 7, pp. 169-176
dc.descriptionFrisch, U., Hasslacher, B., Pomeau, Y., Lattice-gas automata for the Navier-Stokes equation (1986) Physical Review Letters, 56, pp. 1505-1508
dc.descriptionGolberg, D.E., (1989) Genetic Algorithms in Search, Optimization & Machine Learning, , Addison-Wesley, Reading
dc.descriptionGregorio, S.D., Serra, R., An empirical method for modelling and simulating some complex macroscopic phenomena by cellular automata (1999) Future Generation Computer Systems, 16, pp. 259-271
dc.descriptionGutowitz, H., Langton, C., (1988) Methods for Designing 'Interesting' Cellular Automata, , CNLS News Letter
dc.descriptionHillman, D., (1995) Combinatorial Spacetimes, , Ph.D. Thesis, University of Pittsburgh
dc.descriptionIlachinski, H.P., Structurally dynamic cellular automata (1987) Complex Systems, 1, pp. 503-527
dc.descriptionJai, A.E., (1999) Nouvelle approche pour la modélisation des systèmes en expansion spatiale: Dynamique de végétation, Tendences nouvelles en modélisation pour l'environnement, pp. 439-445. , Elsevier, Amsterdam
dc.descriptionKagaris, D., Tragoudas, S., Von Neumann Hybrid Cellular Automata for Generating Deterministic Test Sequences (2001) ACM Trans. On Design Automation of Electronic Systems, 6 (3), pp. 308-321
dc.description(1993) Theory and Applications of Coupled Map Lattices, , Kaneko, K, ed, Wiley, Chichester
dc.descriptionLi, W., (1991) Phenomenology of Non-Local Cellular Automata, , Santa Fe Institute Working Paper 91-01-001
dc.descriptionMaji, P., Ganguly, N., Saha, S., Roy, A.K., Chaudhuri, P.P.: Cellular Automata Machine for Pattern Recognition. In: Bandini, S., Chopard, B., Tomassini, M. (eds.) ACRI 2002. LNCS, 2493, pp. 270-281. Springer, Heidelberg (2002)Mitchell, M., Hraber, P., Crutchfiled, J., Revisiting the edge of chaos: Evolving cellular automata to perform computations (1993) Complex Systems, 7, pp. 89-130
dc.descriptionMitchell, M., Crutchfield, J.P., Das, R., Evolving Cellular Automata with Genetic Algorithms: A Review of Recent Work (1996) Proceedings of the First International Conference on Evolutionary Computation and Its Applications
dc.descriptionNagel, K., Herrmann, H.J., Deterministic models for traffic jams (1993) Physica A, 199, pp. 254-269
dc.descriptionNicolis, G., Prigogine, I., (1977) Self-organization in non-equilibrium systems, , Wiley, Chichester
dc.descriptionOliveira, G.M.B., de Oliveira, P.P.B., Omar, N., Definition and Application of a Five-Parameter Characterization of Unidimensional Cellular Automata Rule Space (2001) Artificial Life, 7, pp. 277-301
dc.descriptionRabino, G.A., Laghi, A.: Urban Cellular Automata: The Inverse Problem. In: Bandini, S., Chopard, B., Tomassini, M. (eds.) ACRI 2002. LNCS, 2493, pp. 349-356. Springer, Heidelberg (2002)Romano, A.L.T., Gomes, L., Gomes, G., Puma-Villanueva, W., Zanetti, M., Von Zuben, C.J., Von Zuben, F.J., Evolutionary Modeling of Larval Dispersal in Blowflies Using Non-Uniform Cellular Automata (2006) IEEE Congress on Evolutionary Computation, pp. 3872-3879
dc.descriptionSchönfisch, B., de Roos, A., Synchronous and asynchronous updating in cellular automata (1999) Biosystems, 51 (3), pp. 123-143
dc.descriptionSchwefel, H.-P., (1981) Numerical Optimization of Computer Models, , Wiley, Chichester
dc.descriptionSipper, M., Non-Uniform Cellular Automata: Evolution in Rule Space and Formation of Complex Structures (1994) Artificial Life IV, pp. 394-399. , MIT Press, Cambridge
dc.descriptionToffoli, T., Margolus, N., (1987) Cellular automata machines - A new environment for modeling, , MIT Press, Cambridge
dc.descriptionTomassini, M., Perrenoud, M., Cryptography with cellular automata (2001) Applied Soft Computing, 1 (2), pp. 151-160
dc.descriptionTomassini, M., Sipper, M., Zolla, M., Perrenould, M., Generating high-quality random numbers in parallel by cellular automata (1999) Future Generation Computer Systems, 16, pp. 291-305
dc.descriptionTsalides, P., Cellular automata based build-in self test structures for VLSI systems (1990) IEE-Electronics Letters, 26 (17), pp. 1350-1352
dc.descriptionVassilev, V.K., Miller, J.F., Fogarty, T.C., The Evolution of computation in coevolving demes of non-uniform cellular automata for global synchronization (1999) Proceedings of the 5th European Conference on Artificial Life, , Berlin
dc.descriptionVon Neumann, J., The General and Logical Theory of Automata, John von Neumann: Collected Works (1961) Design of Computer, Theory of Automata and Numerical Analysis, 5. , Taub, A.H, ed, Pergamon Press, Oxford
dc.descriptionWolfram, S., (1994), Cellular Automata and Complexity, Collected Papers. Addison-Wesley Publishing Company, Reading
dc.languageen
dc.publisherSpringer Verlag
dc.relationStudies in Computational Intelligence
dc.rightsfechado
dc.sourceScopus
dc.titleSynthesis Of Spatio-temporal Models By The Evolution Of Non-uniform Cellular Automata
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución